code: def test_get_embedding_layer_initializes_unseen_words_randomly_not_zero(
      self,
  ):
      vocab = Vocabulary()
      vocab.add_token_to_namespace("word")
      vocab.add_token_to_namespace("word2")
      embeddings_filename = str(self.TEST_DIR / "embeddings.gz")
      with gzip.open(embeddings_filename, "wb") as embeddings_file:
          embeddings_file.write("word 1.0 2.3 -1.0\n".encode("utf-8"))
      params = Params(
          {"pretrained_file": embeddings_filename, "embedding_dim": 3}
      )
      embedding_layer = Embedding.from_params(params, vocab=vocab)
      word_vector = embedding_layer.weight.data[
          vocab.get_token_index("word2")
      ]
      assert not numpy.allclose(
          word_vector.numpy(), numpy.array([0.0, 0.0, 0.0])
      )
  
imports: import gzip
  import warnings
  import numpy
  import pytest
  import torch
  from allennlp.common import Params
  from allennlp.common.checks import ConfigurationError
  from allennlp.common.testing import AllenNlpTestCase
  from allennlp.data import Vocabulary
  from allennlp.modules.token_embedders.embedding import _read_pretrained_embeddings_file, Embedding, EmbeddingsTextFile, format_embeddings_file_uri, parse_embeddings_file_uri
label_desc: Use image node_id 4 for calling the TestEmbedding obj's underlying member method code with example usage: obj.test_get_embedding_layer_initializes_unseen_words_randomly_not_zero() without return types